A macaque connectome for large-scale network simulations in The Virtual Brain
Kelly Shen, Gleb Bezgin, Michael Schirner, Petra Ritter, Stefan Everling and Anthony R McIntosh
Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in the VirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of the VirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.